Please use this identifier to cite or link to this item: http://hdl.handle.net/1893/15717
Appears in Collections:Computing Science and Mathematics Journal Articles
Peer Review Status: Refereed
Title: A graph-based hyper-heuristic for educational timetabling problems
Author(s): Burke, Edmund
McCollum, Barry
Meisels, Amnon
Petrovic, Sanja
Qu, Rong
Contact Email: e.k.burke@stir.ac.uk
Keywords: Heuristics
Graph heuristics
Hyper-heuristics
Tabu search
Timetabling
Operations Research/Decision Theory
Organization/Planning
Information retrieval
Issue Date: Jan-2007
Date Deposited: 1-Jul-2013
Citation: Burke E, McCollum B, Meisels A, Petrovic S & Qu R (2007) A graph-based hyper-heuristic for educational timetabling problems. European Journal of Operational Research, 176 (1), pp. 177-192. https://doi.org/10.1016/j.ejor.2005.08.012
Abstract: This paper presents an investigation of a simple generic hyper-heuristic approach upon a set of widely used constructive heuristics (graph coloring heuristics) in timetabling. Within the hyper-heuristic framework, a tabu search approach is employed to search for permutations of graph heuristics which are used for constructing timetables in exam and course timetabling problems. This underpins a multi-stage hyper-heuristic where the tabu search employs permutations upon a different number of graph heuristics in two stages. We study this graph-based hyper-heuristic approach within the context of exploring fundamental issues concerning the search space of the hyper-heuristic (the heuristic space) and the solution space. Such issues have not been addressed in other hyper-heuristic research. These approaches are tested on both exam and course benchmark timetabling problems and are compared with the fine-tuned bespoke state-of-the-art approaches. The results are within the range of the best results reported in the literature. The approach described here represents a significantly more generally applicable approach than the current state of the art in the literature. Future work will extend this hyper-heuristic framework by employing methodologies which are applicable on a wider range of timetabling and scheduling problems.
DOI Link: 10.1016/j.ejor.2005.08.012
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